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G D Stormo

Publications and source records attributed to G D Stormo.

66 records · Page 4Linked to original sources
PubMed1988

Autogenous regulatory site on the bacteriophage T4 gene 32 messenger RNA.

We have identified the binding site on the bacteriophage T4 gene 32 mRNA responsible for autogenous translational regulation. We demonstrate that this site is largely unstructured and overlaps the initiation codon of gene 32 as previously predicted. Co-operative binding of gene 32 protein to this site specifically blocks the formation of 30 S-tRNA(fMet)-gene 32 mRNA ternary complexes and initiation of translation. The translational operator is bound co-operatively by gene 32 protein and this binding is facilitated by a nucleation site far upstream from the initiation codon. A similar unstructured mRNA lacking this nucleation site is also bound co-operatively, but only at concentrations of gene 32 protein higher than those needed to repress binding of ribosomes to the gene 32 mRNA. Some sequence-specific interactions may also influence this binding. Comparison of the bacteriophage T2, T4 and T6 gene 32 operator sequences leads us to propose that the nucleation site is a pseudoknot.

Base Sequence↗
PubMed1986

Quantitative analysis of the relationship between nucleotide sequence and functional activity.

Matrices can be used to evaluate sequences for functional activity. Multiple regression can solve for the matrix that gives the best fit between sequence evaluations and quantitative activities. This analysis shows that the best model for context effects on suppression by su2 involves primarily the two nucleotides 3' to the amber codon, and that their contributions are independent and additive. Context effects on 2AP mutagenesis also involve the two nucleotides 3' to the 2AP insertion, but their effects are not independent. In a construct for producing beta-galactosidase, the effects on translational yields of the tri-nucleotide 5' to the initiation codon are dependent on the entire triplet. Models based on these quantitative results are presented for each of the examples.

Base Sequence↗
PubMed1986

Information content of binding sites on nucleotide sequences.

Repressors, polymerases, ribosomes and other macromolecules bind to specific nucleic acid sequences. They can find a binding site only if the sequence has a recognizable pattern. We define a measure of the information (R sequence) in the sequence patterns at binding sites. It allows one to investigate how information is distributed across the sites and to compare one site to another. One can also calculate the amount of information (R frequency) that would be required to locate the sites, given that they occur with some frequency in the genome. Several Escherichia coli binding sites were analyzed using these two independent empirical measurements. The two amounts of information are similar for most of the sites we analyzed. In contrast, bacteriophage T7 RNA polymerase binding sites contain about twice as much information as is necessary for recognition by the T7 polymerase, suggesting that a second protein may bind at T7 promoters. The extra information can be accounted for by a strong symmetry element found at the T7 promoters. This element may be an operator. If this model is correct, these promoters and operators do not share much information. The comparisons between R sequence and R frequency suggest that the information at binding sites is just sufficient for the sites to be distinguished from the rest of the genome.

Bacterial Proteins↗
PubMed1986

Sequence landscapes.

We describe a method for representing the structure of repeating sequences in nucleic-acids, proteins and other texts. A portion of the sequence is presented at the bottom of a CRT screen. Above the sequence is its landscape, which looks like a mountain range. Each mountain corresponds to a subsequence of the sequence. At the peak of every mountain is written the number of times that the subsequence appears. A data structure called a DAWG, which can be built in time proportional to the length of the sequence, is used to construct the landscape. For the 40 thousand bases of bacteriophage T7, the DAWG can be built in 30 seconds. The time to display any portion of the landscape is less than a second. Using sequence landscapes, one can quickly locate significant repeats.

DNA, Viral↗
PubMed1984

lacZ translation initiation mutations.

Sixteen single point mutations near the beginning of the lacZ gene have been isolated and their effect on lacZ expression has been measured. Five mutations were obtained that alter a potential stem-and-loop structure in the messenger RNA that masks the initiation codons. Formation of this stem-and-loop is a result of transcription of DNA sequences introduced during the cloning of the lac regulatory region. The mutations isolated were then moved into a background that deleted this structure. Analysis of these mutations indicated that the secondary structure inhibited lacZ expression 5.8-fold and that either single point mutations or a 9 base-pair deletion could relieve this inhibition completely. In addition, it was found that an A to C transversion in the first base following the initiation codon (in the absence of the inhibitory secondary structure) decreases lacZ expression almost twofold, whereas C to U transitions in the next two positions have negligible effects. Mutations were also obtained that either increase or decrease the length of the Shine-Dalgarno sequence. The effects of these mutations were studied in the presence or absence of the secondary structure that involves the two initiation codons. It was found that when translation initiation was inhibited by the secondary structure, increasing the length of the Shine-Dalgarno sequence increased lacZ expression 2.8-fold and decreasing the length of this sequence reduced lacZ expression 12-fold. When translation initiation was not inhibited by the secondary structure, increasing the length of the Shine-Dalgarno sequence had no effect and decreasing the length of this sequence only reduced lacZ expression sixfold. The mechanistic implications of these results are discussed. Two initiation codons are located in the beginning of the lacZ gene, 7 and 13 bases from the Shine-Dalgarno sequence. NH2-terminal sequence analysis indicated that the majority of the protein synthesized initiate at the first initiation codon in the wild-type lacZ gene (in agreement with results reported previously by J. L. Brown and his colleagues). Upon introduction of sequences that result in a change in the mRNA secondary structure, both initiation codons are used in almost equal amounts. Three mutations and two pseudorevertants were obtained, which are located in the first initiation codon. It was found that when the first initiation codon is changed from AUG to GUG, translation initiation is decreased tenfold at that codon.(ABSTRACT TRUNCATED AT 400 WORDS)

Base Sequence↗
PubMed1984

Delila system tools.

We introduce three new computer programs and associated tools of the Delila nucleic-acid sequence analysis system. The first program, Module, allows rapid transportation of new sequence analysis tools between scientists using different computers. The second program, DBpull, allows efficient access to the large nucleic-acid sequence databases being collected in the United States and Europe. The third program, Encode, provides a flexible way to process sequence data for analysis by other programs.

Base Sequence↗
PubMed1982

Characterization of translational initiation sites in E. coli.

We characterize the Shine and Dalgarno sequence of 124 known gene beginnings. This information is used to make "rules" which help distinguish gene beginning from other sites in a library of over 78,000 bases of mRNA. Gene beginnings are found to have information besides the initiation codon and Shine and Dalgarno sequence which can be used to make better "rules".

Base Composition↗
PubMed1982

Use of the 'Perceptron' algorithm to distinguish translational initiation sites in E. coli.

We have used a "Perceptron" algorithm to find a weighting function which distinguishes E. coli translational initiation sites from all other sites in a library of over 78,000 nucleotides of mRNA sequence. The "Perceptron" examined sequences as linear representations. The "Perceptron" is more successful at finding gene beginnings than our previous searches using "rules" (see previous paper). We note that the weighting function can find translational initiation sites within sequences that were not included in the training set.

Base Sequence↗
PubMedDate not supplied

Identifying DNA and protein patterns with statistically significant alignments of multiple sequences.

MOTIVATION: Molecular biologists frequently can obtain interesting insight by aligning a set of related DNA, RNA or protein sequences. Such alignments can be used to determine either evolutionary or functional relationships. Our interest is in identifying functional relationships. Unless the sequences are very similar, it is necessary to have a specific strategy for measuring-or scoring-the relatedness of the aligned sequences. If the alignment is not known, one can be determined by finding an alignment that optimizes the scoring scheme. RESULTS: We describe four components to our approach for determining alignments of multiple sequences. First, we review a log-likelihood scoring scheme we call information content. Second, we describe two methods for estimating the P value of an individual information content score: (i) a method that combines a technique from large-deviation statistics with numerical calculations; (ii) a method that is exclusively numerical. Third, we describe how we count the number of possible alignments given the overall amount of sequence data. This count is multiplied by the P value to determine the expected frequency of an information content score and, thus, the statistical significance of the corresponding alignment. Statistical significance can be used to compare alignments having differing widths and containing differing numbers of sequences. Fourth, we describe a greedy algorithm for determining alignments of functionally related sequences. Finally, we test the accuracy of our P value calculations, and give an example of using our algorithm to identify binding sites for the Escherichia coli CRP protein. AVAILABILITY: Programs were developed under the UNIX operating system and are available by anonymous ftp from ftp://beagle.colorado.edu/pub/consensus.

Algorithms↗